In recent years, the analysis of Big Data has been lauded for its ability to solve complex operational problems, provide meaningful insights, and draw connections across disparate or nuanced sources. Big Data, however, may not be the most effective tool of analysis across all settings. Particularly, within smaller tech operations, the lack of resources required to fully formulate, maintain, and analyze large data sets may limit the benefits of Big Data. Faced with this problem, Steinhardt Technology Services (a small IT Help Desk within New York University) endeavored to develop data strategy that would allow the team to leverage big data insights without the complications of gathering and analyzing Big Data.
In this paper, the author will discuss the development of Sheinhardt Technology Services’s data strategy. The paper will first describe Steinhardt Technology Services’s data dilemma and how creating and executing an intentional data strategy allowed the group to collect and process meaningful help desk data. Next, the author will describe how the data strategy was leveraged to create and maintain the business practices that maximize Steinhardt Technology Services’s ability to execute its mission statement. Finally, the author will discuss future goals and challenges for Steinhardt Technology Services’s data strategy.
